### The Dendrochronology Program Library in R (dplR)

dplR is a software package in the R statistical programming environment for tree-ring analyses. R is the world's preeminent open-source statistical computing environment where users can contribute packages, which are freely available on the internet. dplR can read standard format files and perform several standard analyses. These include interactive detrending, chronology building, and calculating standard descriptive statistics. The package can also produce a variety of publication quality plots. dplR is actively and lovingly developed by a half dozen people in several countries.

*Image: A continuous wavelet transform of a long tree-ring crhonology produced by the wavelet.plot() function*

### dplR Publications

There are two papers that describe dplR:

- Bunn, A.G. 2010. Statistical and visual crossdating in R using the dplR library.
*Dendrochronologia*28: 251-258. - Bunn, A.G. 2008. A dendrochronology program library in R (dplR).
*Dendrochronologia*26: 115-124.

PDFs of these papers can be found on Andy Bunn's ResearchGate profile. Please cite R and dplR properly when using the package. The citation() function in R gives information for how to cite R and its packages:

R> citation()

R> citation("dplR")

We, the developers, enjoy writing this software and helping users. However, we aren't among the idle rich. Alas. We have jobs and occasionally have to answer to our betters. When our department chairs and deans accuse us of being dilettantes we can point to the use of dplR as a partial excuse.

### Source Code

The published library is available on the Comprehensive R Archive Network. There you can download the source code or precompiled binaries for the current release. Within R, dplR can be installed, loaded, and the help pages can be seen via:

R> install.packages("dplR")

R> library(dplR)

R> ?dplR

### Getting Help

The best help you can get is to start using dplR and R. The manual for dplR comes with the installation but is also here. The code linked below for the dplR workshop is illustrative as are the appendicies in the papers written above (Bunn 2008 and 2010). We've started documenting common processing steps using vignettes as well.

### Vignettes

There are, at the moment, two and a half vignettes developed to help folks learn dplR. You can list dplR's vignettes via:

R> vignette(package="dplR")

And view them as:

R> vignette("intro-dplR")

R> vignette("xdate-dplR")

R> vignette("timeseries-dplR")

### dplR Workshop

There are occasional workshops on dplR. E.g., here is the archived code from the 2016 AmeriDendro conference in Mendoza.

### Updating dplR

dplR is updated regularly. Please update to the current version from time to time. It's good R practice:

R> update.packages()

### Development Version

The current development version of dplR can be found on R-Forge. There are several developers actively working on dplR and contributing code. Please let us know what features you would like to see added and report any bugs. You can get a (potentially unstable) daily snapshot of the development version of dplR in R via:

R> install.packages("dplR", repos="http://R-Forge.R-project.org")